Towards ecosystem accounts for Rwanda: Tracking 25 years of change in flows and potential supply of ecosystem services

Abstract

Rwanda, a small but rapidly developing central African nation, has undertaken development of natural capital accounts to better inform its economic development through the World Bank's Wealth Accounting and Valuation of Ecosystem Services (WAVES) Partnership. In this paper, we develop ecosystem service (ES) models to quantify ecosystem condition and physical supply components of ecosystem accounts in Rwanda from 1990 to 2015. We applied the InVEST carbon storage, sediment delivery ratio, nutrient delivery ratio, and annual and seasonal water yield models to map changes in potential ES supply nationwide. We also quantified flows of sediment, water and nutrients to 96 hydroelectric dam, irrigation dam and water treatment plant sites. Over a 25‐year period, we found declines in all ES, which were most strongly driven by conversion of forests to cropland. Declines were most pronounced from 1990 to 2000 and 2010 to 2015; ES were relatively stable from 2000 to 2010 (with the exception of nutrient exports to water bodies, which jumped most sharply from 2000 to 2010). From 2010 to 2015, over 42% of Rwanda's water‐use sites (representing 9% of the nation's hydroelectric generation capacity and 59% of its water treatment capacity) had upstream increases in sediment export and quick flow greater than the national average. Half of Rwanda's water treatment plants had upstream phosphorus exports greater than the national average. Our results quantify nation‐wide ES trends, their implications for key water‐dependent industries, and the importance of protected areas in safeguarding ES flows and potential supply in Rwanda. They also provide data that can be integrated with existing land, water and economic accounts for Rwanda, as well as a baseline to inform development strategies that better link economic and environmental goals. A free Plain Language Summary can be found within the Supporting Information of this article.

Global socio-economic impacts of changes in natural capital and ecosystem services: State of play and new modeling approaches

“…As ecosystem accounting in the SEEA EEA framework is relatively new, there are an increasing number of examples, for 24 countries at last count (Hein et al, 2020a), at various scales and for different services, including the development of physical and monetary supply and use accounts for the Netherlands as a whole (CBS and WUR, 2015;Hein et al, 2020b) and ES supply and use accounts in Rwanda at the national and provincial level (Bagstad et al, 2020). Hein (2014) and Crossman et al (2013) provide a useful overview of simple to complex biophysical modeling approaches for estimating ES supply in an ecosystem accounting context consistent with SEEA, which can be scaled up to the global level while maintaining consistency.…”

“…IEEM captures the dynamics of provisioning ecosystem services as inputs into economic processes and the returns to the environment in terms of emissions and waste. The IEEM Platform integrates nonmaterial regulating and cultural and aesthetic ecosystem services by linking IEEM with spatial ES modeling (IEEM + ESM) (Bagstad et al, 2020;Banerjee et al, 2019bBanerjee et al, , 2019c. The linkage between the economic and spatial ES modeling components is made possible thorough LULC change modeling which is used to spatially allocate IEEM demand for land across a high-resolution spatial grid to produce LULC projections for a baseline and policy scenarios.…”

“…The IEEM Platform linked with ES modeling-IEEM + ESM-is one such complex systems approach that leverages the benefits of the consistency between SEEA and SNA to generate spatially explicit estimates of key indicators of sustainable economic development, including wealth and natural capital metrics. The OPEN IEEM initiative adopts a paradigm of open sharing of data and models and FAIR data principles which will contribute to shifting efforts toward methodological innovation and stronger analysis and away from replicating efforts of previous work (Bagstad et al, 2020;Banerjee et al, 2019a).…”

Assessment of Switchgrass-Based Bioenergy Supply Using GIS-Based Fuzzy Logic and Network Optimization in Missouri (U.S.A.)

“…The carbon storage model matches land cover to estimate carbon pools in soil, above-ground and below-ground biomass, and woody debris using a lookup table. The sediment delivery ratio model computes total sediment generated, sediment export, sediment retention using the universal soil loss equation (USLE) combined with a connectivity index [55]. We used LULC maps in three scenarios, including base, scenario 1, and scenario 2, as LULC inputs of models to compare between scenarios.…”

Trends in Ecosystem Services across Europe Due to Land-Use/Cover Changes

“…Aggregating LULC types: We used the CORINE Land Cover (CLC) [53,54] A2). Since some LULC types were missing in Tasser et al [7], we integrated ES values from other studies [52,55,56]. Moreover, we distinguished raster cells with slope < and ≥30 • for a refined mapping of protection from hazards (R1) by adapting ES supply [57,58] and set the sociocultural preference to 1 in areas with a slope below 30 • , as there is no demand for this ES.…”